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Know How With Boosting Algorithm The Accuracy Of Machine Learning Model Can Be Increased?

- Create many (e.g. 100) random sub-samples of our dataset with replacement (meaning we can select the same value multiple times).
- Learn(train) a decision tree on each sample.
- Given new dataset, Calculate the prediction for each sub-sample.
- Calculate the average of all of our collected predictions(also called bootstrap estimates) and use that as our estimated prediction for the data.
- The procedure can be used in similar way for classification trees. For example, if we had 5 decision trees that made the following class predictions for an input sample: blue, blue, red, blue and red, we would take the most frequent class and predict blue.